|Publication number||US7546419 B2|
|Application number||US 11/141,958|
|Publication date||Jun 9, 2009|
|Filing date||Jun 1, 2005|
|Priority date||Jun 1, 2004|
|Also published as||US20050268044|
|Publication number||11141958, 141958, US 7546419 B2, US 7546419B2, US-B2-7546419, US7546419 B2, US7546419B2|
|Inventors||Blaise Aguera y Arcas|
|Original Assignee||Aguera Y Arcas Blaise|
|Export Citation||BiBTeX, EndNote, RefMan|
|Patent Citations (67), Non-Patent Citations (11), Referenced by (3), Classifications (17), Legal Events (6)|
|External Links: USPTO, USPTO Assignment, Espacenet|
This application claims the benefit of U.S. Provisional Patent Application Ser. No. 60/575,987, filed Jun. 1, 2004, entitled “The Zeno cache: a system for increasing the effectiveness of most-recently-used (MRU) caching for variably compressable data objects,” the entirety of the disclosure of which application is hereby incorporated herein by reference.
“MRU caching,” where MRU stands for “most recently used,” is a known concept for implementing a client-side memory in a client-server system. It is assumed that the server has access to and can serve to a client a large number of data objects, which in the aggregate may occupy a large amount of memory. The available bandwidth between client and server is limited, however, so client requests for data objects to be sent from the server take time. If access to data objects is reasonably “coherent,” meaning that objects which the client needed recently are likely to be needed again in the near future, then MRU caching may increase the efficiency of the client-server system. Employing this approach, the client generally sets aside some limited amount of memory (generally much less than would be needed to store all of the objects on the server), and stores in this memory (a cache) as many of the most recently requested objects as will fit. When a new object is sent from the server to the client and the client's cache space has run out, the least recently used (LRU) object is erased from the cache to create data storage space in which the new object may be stored.
Generally, when the client needs a data object, the cache is first examined to see if the object is cached. If it is cached, then the cached representation is used, obviating the need for a slow or computationally expensive server request. Usually, making use of a cached representation also “promotes” that object to the MRU end of the cache. This approach generally provides substantial performance advantages over having to request data from the server for every data object accessed.
The erasure of the least recently used object from a cache when a new object is accessed by a computing system and stored in the cache may cause inefficiency in cache usage. Even the erased, least-recently-used object in the cache may be again requested by the server. When this happens, the server may undertake the relatively slow or computationally expensive task of retrieving this object from a more remote source of data storage, such as a main memory or mass storage device. Given the finite size of cache memories, object erasure may occur with some frequency, thereby causing a server or other computing system to expend significant resources accessing more remote memories to get data that was once conveniently stored in a cache memory. Accordingly, there is a need in the art for a more efficient and flexible approach to cache memory management.
According to one aspect, the invention may provide a method, comprising providing a cache in a computing system having an initial group of cache objects, each cache object having an initial compression ratio and including stored data; decreasing an amount of data storage space occupied by at least one of the cache objects other than a given one of the cache objects; and increasing an amount of data storage space occupied by the given cache object. Preferably, the decreasing comprises decreasing the amount of data storage space by a given amount. Preferably, the increasing comprises increasing the amount of data storage space occupied by the given cache object by the given amount. Preferably, the decreasing comprises increasing the initial compression ratio of the at least one cache object. Preferably, the increasing comprises decreasing the initial compression ratio of the given cache object. Preferably, the given cache object is a most recently used cache object of the cache objects. Preferably, the at least one cache object undergoing the decreasing step comprises a least recently used cache object of the cache objects.
Preferably, the decreasing comprises removing a portion of the stored data for the at least one cache object. Preferably, the increasing comprises supplementing the stored data for the given cache object. Preferably, an amount of data storage space available for each of the cache objects may equal one of a finite number of discrete values. Preferably, the decreasing comprises reducing the amount of data storage space for at least one randomly selected cache object of the cache objects, other than the given cache object. Preferably, the reducing comprises reducing the amount of data storage space for the at least one randomly selected cache object to a randomly determined extent. Preferably, the randomly selected cache object is selected using one of a random method and pseudorandom method. Preferably, the selection of the randomly selected cache object is guided by a heuristic.
Preferably, the method further comprises storing the given cache object in a losslessly compressed form after the increasing. Preferably, the method further comprises storing the given cache object in uncompressed form after the increasing. Preferably, the decreasing comprises removing at least one of the cache objects other than the given cache object.
According to another aspect, the invention may provide an apparatus, comprising a computing system having at least one processor capable of operative communication with a main memory; and a cache in the computing system having an initial group of cache objects, each cache object having an initial compression ratio and including stored data; wherein the computing system is operable to decrease an amount of data storage space occupied by at least one of the cache objects other than a given one of the cache objects; and increase an amount of data storage space occupied by the given cache object. Preferably, the decreasing comprises decreasing the amount of data storage space by a given amount. Preferably, the increasing comprises increasing the amount of data storage space occupied by the given cache object by the given amount. Preferably, the decreasing comprises increasing the initial compression ratio of the at least one cache object. Preferably, the increasing comprises decreasing the initial compression ratio of the given cache object.
Preferably, the given cache object is a most recently used cache object of the cache objects. Preferably, the decreasing comprises removing a portion of the stored data for the at least one cache object. Preferably, the increasing comprises supplementing the stored data for the given cache object. Preferably, an amount of data storage space available for each of the cache objects may equal one of a finite number of discrete values. Preferably, the decreasing comprises reducing the amount of data storage space for at least one randomly selected cache object of the cache objects, other than the given cache object. Preferably, the reducing comprises reducing the amount of data storage space for the at least one randomly selected cache object to a randomly determined extent.
According to another aspect, the invention provides method, comprising: providing a cache in a computing system, the cache having an initial condition; if insufficient data storage space is present in the cache under the initial condition to store at least one new object in the cache, compressing at least one object in the cache to clear data storage space for the at least one new object; and storing the at least one new object in the cache. Preferably, the initial condition corresponds to the cache being empty. Preferably, the method further comprises continuing to store new objects in the cache without compressing the objects stored in the cache until insufficient data storage space remains in the cache to store any additional new object. Preferably, the method further comprises storing the at least one new object in the cache without the compressing, if sufficient space for storing the at least one new object is present in the cache under the initial condition.
Other aspects, features, advantages, etc. will become apparent to one skilled in the art when the description of the preferred embodiments of the invention herein is taken in conjunction with the accompanying drawings.
For the purposes of illustrating the various aspects of the invention, there are shown in the drawings forms that are presently preferred, it being understood, however, that the invention is not limited to the precise arrangements and instrumentalities shown.
This disclosure makes reference to the LRU and MRU ends of the cache. Objects are generally added at the MRU end, and are generally erased from the LRU end. However, the present invention is not limited to such a scheme. It is noted that the physical layout of cache objects in a cache need not correspond to the LRU-MRU layout. The layout of a cache merely preferably enables a computing system to find, insert, and/or erase objects in the manner described herein. The linear LRU-MRU arrangement is a convenient mechanism for describing the operation of a cache, but represents only one of many possible implementations of a cache memory. Herein, the terms “cache” and “cache memory” are used interchangeably.
It is noted that, although MRU caching and its extensions disclosed herein are discussed in the context of a client/server architecture, similar principles apply to many other scenarios, such as efficient hard disk access on a single computer (where access to the hard disk is slower than access to RAM, and RAM is thus used to cache the most recently used content on the hard disk). In one or more other embodiments, data are gathered from the environment or generated computationally rather than being loaded from a disk or sent across a network. In each case, the client has access to a small but fast temporary cache memory, and a larger but slower data source from which information is requested repeatedly. This slower data source is generally referred to herein as the “server.”
The following discussion of convergent series is provided as an introduction to the cache memory apparatus and method disclosed herein.
The infinite sum of the series y(n)=n^−p, with n going from 1 to infinity, and with p>1, is finite. Similarly, the sum of y=1/b^n is finite for b>1. For example, in the latter case, if b=2, the sum is exactly 2. The principles underlying such convergent series may be used to implement one or more embodiments of efficient data caching methods and apparatus as described herein.
One or more embodiments of the methods and apparatus described herein may employ concepts related to the “Zeno paradox,” which is described below. While this discussion provides a conceptual underpinning applicable to one or more embodiments described herein, the present invention is not limited by the conceptual aspects discussed below.
Zeno Caching Concept.
Zeno is a runner who is so quick that in one step (which, for the sake of discussion, it is assumed he makes every second) he covers half the distance from his current position to the end of any racetrack. The paradox is that he never finishes the course, even though he moves forward with every step. This paradox is easily related to the 1/b^n series above with b=2, and summing from n=2 to infinity. This concept may be extended to the storage of cache objects (with the cache itself being analogized to the “racetrack”) by enabling the cache objects to be compressed to a progressively greater extent with decreasing recency of use or access. Thus, in proceeding from the MRU end of a cache to the LRU end thereof, a theoretically infinite number of additional cache objects of ever decreasing size could be put in place, without ever running out of space. This principle is referred to herein as the Zeno cache concept.
Preferably, the cache objects concerned herein are compressible, which in this disclosure, corresponds to being amenable to lossy data compression techniques. Lossy data compression may be characterized by the ability to represent a data object with fewer bytes than the full representation of the data object. Higher compression ratios generally incur higher distortion of the data object and lower quality of an image rendered using the compressed data (where the object includes one or more image files). Without limitation, lossy compression techniques may also be applicable to sound, video, and many other data types.
In one or more embodiments, compressed versions of the data may be suitable as substitutes for the uncompressed data. Below a given level of distortion, the compressed representations of the data may be fully adequate, and above the given level of distortion, the compressed representations may be adequate as a temporary measure while the client waits for a higher quality version of the data. The higher quality version may merely be less compressed than the temporarily used version, or may be losslessly compressed or uncompressed.
In one or more embodiments, lower quality representations may be subsets of higher quality representations, meaning that improving the representation quality at the client side may involve merely sending data to supplement lower quality representations, thereby providing the higher quality representation. Preferably, with this approach, there is no need to incur the burden of sending an entirely new set of data associated with the high quality representation. This approach preferably avoids redundancy and hence preferably substantially increases efficiency.
Consistent with the approach discussed above, the reverse process of lowering the representation quality of an object may involve merely removing a portion of the data employed for a high quality representation of an image, rather than requiring compression, or re-compression, of the data used for the high quality representation. This property preferably also enhances the efficiency of the caching apparatus and method disclosed herein.
In one or more embodiments, the compression technique may provide objects with compression levels that scale from lossy to lossless. This feature may allow a lossless representation of a data object to be built up in steps, from highly lossy to lossless, at little or no extra total cost relative to sending across a lossless version initially. An example of a data type and compression technology enabling the above features is the wavelet compression of images, as exemplified by the JPEG2000 standard. However, the present invention is not limited the use of the JPEG2000 standard.
Given the above properties, if memory were “continuous” (i.e. not discretized into bytes) then it would be possible in theory to cache an infinite number of data objects in a finite amount of memory, merely by enforcing the constraint that the compressed sizes of the objects conform to the rules of a convergent series as discussed earlier herein. The operation of a cache able to function in accordance with the theory discussed above is described below in connection with
In the graph of
With reference to
In one or more embodiments, the theoretical implementation described above is preferably modified for two reasons. First, in practice, memory storage is preferably composed of discrete storage units. Thus, for example, it is usually meaningless in practice to compress a cache object to occupy an amount of storage space that is smaller than one bit. Second, the total number of operations performed on the cache is preferably finite. In contrast, enforcing a continuous curve of compression ratios described by one of the convergent formulas above may involve reducing the size of every cache object in the cache every time additional cache storage space was needed. This would require an impractically large number of operations.
In one or more embodiments, the number of objects in the cache will in practice be finite. However, where the Zeno cache concept is employed, this number may be much larger than would be possible with conventional MRU caching. Further, cached objects may have the property that if recently used, they may be stored at a high quality level (anywhere from a low level of distortion, or compression lossyness, to lossless compression, to uncompressed data). The quality level of cache objects may become progressively worse (i.e. be subject to progressively higher levels of distortion or compression lossyness) with each successive cache memory access in which these cache objects are not accessed.
Because computer memory is discrete and there may be a minimum compressed size of a cache object below which a cache object may have no value to a user, cached representations may be subject to a maximum compression ratio that yields this minimum compressed size. Thus, in one or more embodiments, the maximum number of cache objects that can be stored in the cache may equal the total data storage space in the cache divided by the amount of data storage space occupied by a cache object having the above-described minimum compressed size, if the objects are all of equal size. However, the cache objects need not all be of equal size.
There are many ways to design a series which is bounded by one of the equations discussed above (or any other convergent sum), and which therefore has a finite sum. An additional constraint can also be introduced, specifically that the likelihood of any given value repeating in successive values of a series increases at higher values of N such that the number of different values of Y employed may be limited to a reasonable number.
An example of such a series is: 1, ¼, ¼, 1/16, 1/16, 1/16, 1/16, 1/64, 1/64, 1/64, 1/64, 1/64, 1/64, 1/64, 1/64, 1/256, etc.
Clearly the sum of the series 1, two quarters, four sixteenths, eight sixty-fourths, etc. is 2, just like y=1/2^n, as discussed earlier herein, But, if we take the series out to n=16000, only about log2(16000), or about 14, values of y (object data storage space size) may be used.
In one or more embodiments, the log function described above provides one way to cause the number of available values of Y (possible sizes of the cache objects) to grow much more slowly than the value of N. However, the present invention is not limited to the use of this log function, and other mathematical operations that cause the number of values of Y to grow more slowly than the value of N may be employed in connection with the present invention.
In one or more embodiments, when N=one million, as few as 20 values of Y may be used (as determined using the logarithm-based formula recited above). This implies that when space has to be freed in the cache, only a small number of operations may be needed to establish a suitable allocation of data storage space among the cache objects, since the majority of the cache objects will occupy an amount of data storage space that preferably does not need to change.
Other mathematical series may also satisfy the desired criteria for use within a cache memory management system and method. Additionally, it is possible to use series that are not theoretically convergent (i.e. whose sums are infinite), since in practice a finite number of terms will be summed in any case.
In one or more embodiments, random algorithms may be used to improve the basic algorithm in a number of ways. In one more embodiments, the 2*¼, 4* 1/16 etc. series, described above, may include only a small number of available cache object sizes, possibly leading to stark differences in compression ratios between different objects within a cache. Random choice may be used to “squeeze” (reduce the data storage space used by) a randomly selected subset of the cache objects in a weighted fashion until some target amount of space is made available for new cache objects. This approach may provide beneficial results because the exact position in the cache of a cache object may decrease in importance with an increasing number of objects in the cache. The amount by which each object is “squeezed” may also be at least partially randomized. Using randomization algorithms like those discussed herein may reduce obvious discontinuities or thresholds in cache-object quality, which may be perceived in images rendered using cache objects stored in the cache.
In the following, an illustrative example of managing cache objects in a data cache in accordance with one or more aspects of the present invention is presented.
In one or more embodiments, including that shown in
At step 602, cache objects 302, 304, 306, 308, and 310 are provided to a program having access to cache 300. The group of cache objects initially present in cache 300 are shown in
At step 604, an indication may be provided as to which cache object will be the next to be used by the program. At step 606, the indicated cache object, which in this example is CO 3 306, may be accessed by the program.
At step 608, a determination may be made as to whether the accessed cache object is expandable. Herein, a cache object is expandable when it may occupy more data storage space by being subject to a lower compression ratio. Such expansion may be accomplished by supplementing the data already present in the cache object rather than by providing a completely new set of data corresponding to the new compression ratio (or corresponding to a lack of compression).
If the accessed cache object is not expandable, it is preferably restored to cache 300 in step 610. Preferably, in step 610, the restored cache object occupies the same amount of data storage space after being accessed as it did prior to such access. Consistent with the principles of LRU-MRU caching, upon being restored to cache 300, the accessed cache object may be written to the rightmost, or MRU end, of cache 300. Alternatively, however, the accessed cache object could be written to any part of cache 300. Continuing with this branch of method 600, the method 600 preferably ends at step 612.
With reference to step 608, if the accessed cache object, such as cache object 306, is expandable, it is preferably expanded (step 614) in accordance with one or more embodiments of the present invention. As previously discussed herein, expanding a cache object as described above preferably helps provide an arrangement in which the most recently and/or the most frequency accessed cache objects are stored in cache 300 at the highest quality levels.
In one or more embodiments, where there are “N” cache objects in a cache, the number of possible sizes (as measured in data storage space) of such cache objects may be limited to the quantity equal to log2(N). Establishing a limited, finite number of possible cache object sizes, as described above, preferably limits the computational expense of determining a new, expanded size for a cache object, such as CO 306, to be expanded in step 614.
In one or more embodiments, the amount of data storage space needed for the expanded (or otherwise stated, less compressed) version of CO 306 may be calculated by a computing system (not shown) having access to cache 300. Where cache 300 is not yet ready to receive the expanded version of CO 306, the expanded version of CO 306 may be written to another memory storage location (not shown) for temporary storage therein.
At step 616, data storage space 402 needed for storing an expanded version of CO 306 is preferably made available within cache 300. If there is sufficient space present within cache 300 to store an expanded version of CO 306 without altering any cache objects within cache 300, then a reduction in size of one or more of the cache objects in cache 300 may be omitted. However, where all or substantially all of the storage space in cache 300 was occupied prior to CO 306 being accessed, one or more of the cache objects other than CO 306 may undergo a reduction in size to free up space in cache 300 for storage of an expanded version of cache 306.
In one or more embodiments, the number of cache object size reduction operations may be reduced where there is a limited number of possible cache object sizes. Limiting the number of cache object size reduction operations preferably operates to reduce the computational burden on a computing system accessing cache 300 and preferably provides for overall computing system efficiency.
In one or more embodiments, there may be various ways to achieve a desired amount of data storage space clearing. Herein, the term “clearing” may correspond to making data storage space available in cache 300 by reducing the data storage space allocated to one or more cache objects within cache 300.
In one or more embodiments, the amount of data storage space to be cleared may correspond to the amount of additional storage needed by the expanded cache object over and above the space it occupied prior to its most recent access by a computing system. However, in other embodiments, the amount of space to be cleared may be smaller or greater than the amount space by which the most recently accessed cache object has increased in size.
In one or more embodiments, the space cleared for the most recently used, expanded cache object may be at one end of cache 300, as is illustrated in
In one or more embodiments, the data storage space to be made available may be provided at the expense of one or more of the cache objects of
In one or more embodiments, the extent of size reduction of the one or more cache objects eligible for size reduction may be selected according one or more considerations. In one embodiment, the cache objects eligible for size reduction may shed an equal or substantially equal amount of storage space. In another embodiment, the eligible cache objects may shed an equal or substantially equal proportion of their pre-reduction size to clear space for the expanded, most recently used cache object.
In one or more other embodiments, the extent of size reduction of each cache object may be based on how recently the cache object was last accessed. Specifically, cache objects eligible for size reduction may shed progressively more storage space with decreasing recency of the last access thereof. Thus, under this approach, the most recently used of the cache objects eligible for size reduction may shed a relatively small amount of storage space, and the least recently used cache object may shed a relatively large amount of data storage space, with those cache objects in between these two extremes shedding intermediate amounts of storage space.
While the discussion of storage space reduction herein is directed primarily to merely reducing the size of cache objects that are not the most recently accessed, in one or more embodiments, one or more cache objects may be removed from cache 300 to clear data storage space. Moreover, such cache object removal may be practiced either alone, or in combination with cache object data storage space reduction of cache objects that will remain within cache 300.
In the embodiment of
In one or more embodiments, rather than managing objects in the cache employing only the recency of use of each cache object as a variable in determining cache object size, cache object management may also involve intelligent guessing about which objects might be needed next. Thus, objects less likely to be needed may be “squeezed” before objects with a higher likelihood of being needed in the future. In one or more embodiments, this guessing approach could be combined with an algorithm that may randomly select objects in the cache for squeezing and which may additionally generate a randomly varying amount of squeezing for the objects selected.
In one or more embodiments, RAM 706 and/or ROM 708 may hold user data, system data, and/or programs. I/O adapter 710 may connect storage devices, such as hard drive 712, a CD-ROM (not shown), or other mass storage device to computing system 700. Communications adapter 722 may couple computing system 700 to a local, wide-area, or Internet network 724. User interface adapter 716 may couple user input devices, such as keyboard 726 and/or pointing device 714, to computing system 700. Moreover, display adapter 718 may be driven by CPU 702 to control the display on display device 720. CPU 702 may be any general purpose CPU.
It is noted that the methods and apparatus described thus far and/or described later in this document may be achieved utilizing any of the known technologies, such as standard digital circuitry, analog circuitry, any of the known processors that are operable to execute software and/or firmware programs, programmable digital devices or systems, programmable array logic devices, or any combination of the above. One or more embodiments of the invention may also be embodied in a software program for storage in a suitable storage medium and execution by a processing unit.
Although the invention herein has been described with reference to particular embodiments, it is to be understood that these embodiments are merely illustrative of the principles and applications of the present invention. It is therefore to be understood that numerous modifications may be made to the illustrative embodiments and that other arrangements may be devised without departing from the spirit and scope of the present invention as defined by the appended claims.
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|U.S. Classification||711/133, 711/118, 711/134, 711/136|
|International Classification||G06F13/00, G06F13/28, G06F12/12, G06F12/08, G06F12/00|
|Cooperative Classification||G06F12/0875, G06F12/0886, G06F12/0866, G06F12/127, G06F12/121, G06F2212/401|
|European Classification||G06F12/12B6B, G06F12/12B|
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